Customer service automation uses software in performing tasks in the customer service to make the service better and faster for customers and agents.
Most often this is done through using Artificial Intelligence (Conversational AI). Automating customer service entails automated chatbots or Virtual Customer Assistants for quicker support, personalized product recommendations, speech-detecting IVRs for intelligent routing, call center call transcription and agent-assist support systems for providing information about customer issues.
A while back customer service meant a call center staffed with several agents, where the customer could be routed to a person in the call center by either their company or the human agent was busy and unable to assist.
The person in the call center would then be assigned the call to help the customer and transfer the customer to another representative if needed. Calls were then assigned to multiple agents, one for each queue in the call center. The individual would then be assigned the call and manage its progress to get the customer assistance. Often the number of agents was so high that people used their break times for answering incoming calls.
Nowadays customers engage with companies across a variety of channels. In addition to calling, customers use emails, messaging (Messenger, WhatsApp), SMS (or text messages), live chat on websites and new channels like RCS and Apple Business Chat.
As there are more and more channels available for the customers to contact companies, call center agents become increasingly overworked as they have to switch between answering calls, text messages, Facebook messages and doing live chat.
As such automation is needed for reducing the burden of call center agents and providing customers with a delightful user experience that is immediate and accurate.
Customer service automation has many benefits. As is often the case, during the process of dealing with companies, customers are forced to wait on hold, respond to automated phone prompts and wait for the company to email them back.
This results in customers feeling like they've been ignored and as a result they can end up taking their business elsewhere. The following is a list of benefits that customer service automation can bring.
By far the fastest growing channel of interacting with customer service systems is through a chat interface. A chat system is used because it is fast, intuitive and it can keep up with the highest ever demand for customer service.
Chatbots and intelligent virtual assistants bring efficiencies to customer service departments because customer service chatbots can answer questions immediately and in multiple languages. Being able to provide sub 1-second answers pleases customers that are looking for the quickest answers to their problems.
Connecting AI based chatbots into existing back office systems means that the chatbot can do the bulk of the work for the customer service teams.
By authenticating the customer, the chatbot is able to provide personalized information about things like invoice payments, order status, available discounts, any trouble with specific services or products used.
All this provides customers detailed information about their queries and is something that previously only customer support agents could handle.
Another benefit of having self-serve channels is the ability for customers not having to wait for agents. Agents need to be available for the next available customer as much as possible but it is possible for the agents to have too many in-bound requests so that customers have to wait a long time.
A benefit for an automated customer support system is that it does not really have an upper limit on capacity. And it is becoming easier to build a chatbot with no-code tools in a simple step-by-step process. By understanding customer requests through intent detection and Natural Language Processing, chatbots can self-serve customers.
Chatbots can become a master of the conversation by being intelligent about what information is required and what actions to take. Chatbots can build a positive experience for customers and establish trust by answering common FAQs. This translates into decreased work for customer service agents.
There are in general 4 metrics you should keep an eye on when developing your chatbot in customer support. Average deflection rates by using chatbots hover around 50%. This translates into reducing customer service agents’ workload by 50%.
By learning what customers want to buy, chatbots automating customer service can upsell and cross-sell products and services. As an example, when a user asks about roaming fees from its telecom provider and is satisfied with the answer, the bot can suggest to purchase a new phone that comes discounted with a data plan.
Chatbots store the conversation with customers so that when customers are forwarded to agents, this conversation history gets forwarded as well.
Many providers allow for this feature and it is highly beneficial because then the agent can quickly read through the conversation between the bot and the user and start solving the question without asking the customer to repeat itself.
Many chatbots in the market are designed with business logic, like recommending products to customers or delivering information about a website visitor, which can contain useful business insight.
One of the major challenges with the traditional business intelligence solutions is that the data is locked inside the system as audio files where insight is difficult to gather. With chatbots the data is already in text format and using either the chatbot software vendor’s analytics or business intelligence tools it is possible to discover valuable insights.
Things such as customer behavior, preference for products, feedback to services, common issues with using services, common complaints and what products serve the most value and satisfaction.
The main driver for increased customer happiness is that the chatbot can give the customer a quick answer. When a customer usually contacts a business they are either put on hold in the call center or their email sent to info@company.com address gets a response in a few days.
Immediate answer from the bot increases customer happiness and if it gives the exact information customers are looking for then the benefits to the company can be significant in terms of customer loyalty.
Of course, one should be mindful that all customer service automation products should be built with high quality. If you roll out a sub-par chatbot with poor design, poor language training and poor answers, your customers might get angry.
Same goes for IVRs with too many menu options and being assigned to hold in a queue at the end of the user journey.
It is highly recommended that you analyze carefully where and how you want to place your customer service automation tool. Think from the point of view of the customer. If it is something that you would enjoy using, it is likely that your customers would too.
When you start automating customer service make sure you first have a business case in mind. This means having a financial metric that you can tie directly to your customer service automation project.
This can be costs saved, decreased time to resolution, increased revenue from additional personalized sales etc. Whatever it is, have a metric, your “North Star”, that you can objectively determine whether your automation project is producing results.
Now, once you have your metric then here are some of the specific things you can do to automate your customer service operations.
The simplest form is a customer service chatbot. A chatbot is an interface through which the user can obtain information from the machine. The interface is usually in written form (chat) and in many cases the chatbot presents the user information with simple Yes/No type of options.
These if-else statements are essentially decision trees where the user selects a certain answer. Upon the selection of that answer the user is given a follow-up question with a choice of answers again.
An improvement upon a chatbot is what's called a Virtual Customer Assistant (VCA). These intelligent agents are not only capable of presenting a multiple choice selection of answers to the user but also understand user intent from free text.
Understanding natural language and being able to interact in multiple languages is a significant leap. While most VCA require technical skills to be built there are emerging platforms that support the no-code approach to building VCAs where no coding skills are needed.
Using AI for customer service in the call center can be done in a variety of ways. It used to be that when calling customer support the main form for customers to reach human support was through pressing buttons on their phones.
Now companies have deployed digital forms of IVRs where customers just speak and tell what their problem is.
An example of AI powered customer service is making use of analyzing what customers have talked over the phone with customer support agents. Such technologies are capable of transcribing speech into text and then analyzing what customers actually wanted.
This provides various information into what were the customers' problems and what type of information they were looking for.
AI also helps customer service agents provide better support. These so-called co-pilot modes assist agents when they are on the phone or chatting with customers. AI is analyzing information provided by the customer and from that they can provide answers that the customer service agent should tell the customers.
Authentication in the context of customer service usually means authenticating through a combination of a sign-up ID and a password. It is also possible to use voice authentication. Here the algorithms are listening on how the customer is speaking. This means that the AI is looking at the tone, cadence and pitch of the voice of the customer. Based on those parameters the algorithms create a user profile and use it as a method of authenticating the customer.
While customer service automation does allow you to streamline and streamline your customer service operations, it does not guarantee that the benefits will be on par with other customer service activities.
What does determine the success of customer service automation is the ability to clearly measure and quantify the outcomes of your efforts. This will enable you to gauge the ROI of your investment as well as the incremental benefits that are coming from the use of customer service automation.
There are a number of metrics that are important when determining the success of customer service automation. Here is a detailed list of the key Conversational AI customer service automation metrics.
Here are some of the specific things you want to measure is:
There are many companies offering customer service automation software and their platforms are available in different versions with varying feature sets and pricing structures.
Below we have listed the top customer service AI software companies.
AlphaChat is a no-code end-to-end Conversational AI platform allowing anyone to build Natural Language Understanding Intelligent Virtual Assistants. The platform also offers advanced features for enterprise customers such as authentication, SSO, APIs, agent co-pilot mode and intelligent routing.
Top Features:
What’s special about this tool: Standard Package offers everything from to build your own AI. insights into customer conversations (topics discussed, customer satisfaction) and statistics on AI value performance. Enables to train the NLU chatbot in one language and have it automatically chat in any language. SLAs and AlphaOS with DIY custom code writing available for enterprise accounts.
Pricing: 10-day free trial. Paid plans from €399/month.
Amelia (from IPSoft) is an AI software company that allows building job-based digital employees for external and internal customer support.
Top Features:
What’s special about this tool: Amelia is a no-code AI platform for creating digital assistants for a variety of use cases including internal IT and support.
Pricing: Price available on request.
Zendesk Answer Bot is a platform from the contact center software provider that allows building chatbots for support automation with the Flow Builder.
Top Features:
What’s special about this tool: Zendesk Answer Bot is a tool for building a quick bot to answer common questions and escalate complex queries to the agents.
Pricing: Paid plans from €49/agent/month includes up to 50 AI-powered automated answers.
IBM Watson Assistant offers speech-to-text and chat automation capabilities for building your virtual customer assistants for customer support.
Top Features:
What’s special about this tool: IBM Watson Assistant brings a variety of machine learning tools and capabilities for automating your customer support from chat to voice to internal data.
Pricing: Free up to 5 skills and 10,000 messages/month. Paid plans from $120/month.
Dialogflow is a Natural Language Understanding engine from Google to connect with your chatbot.
Top Features:
What’s special about this tool: Dialogflow NLU can be integrated in several 3rd party Conversational AI platforms.
Pricing: Essentials edition $0.002/request, CX edition $20 per 100 chat sessions.
The fact that customer service is not just about the user support, but also the whole relationship, serves as a reminder that it should be handled by skilled support agents who know the product, its audience and its mind set.
AI can help in customer service automation through natural language understanding chatbots, call transcription, authentication and analytics. Make sure you know what metrics you wish to improve with AI to achieve the various benefits that come with using AI in automation (e.g. quicker response times, personalized answers, reduced wait times for customers).
Considering the benefits offered by customer service automation, the use of AI is gradually becoming the more preferred option for most companies to make their support more efficient and user-friendly.
If you are looking for AI chatbots for your customer service, then feel free to sign-up for an account with alphachat.ai In just a few minutes you can get your own natural language understanding AI chatbot that you can connect with your website.
